System and process for image rescaling using adaptive interpolation kernel with sharpness and de-ringing control

ABSTRACT

A digital video rescaling system is provided. The system includes an image data input configured to receive input support pixels y 1  to y n  and a sharpness control module configured to generate a sharpness control parameter Kshp. The system further includes an interpolated pixel generator configured to use an adaptive interpolation kernel to generate an interpolated pixel y s  based on the input support pixels, and adjust a sharpness of the interpolated pixel y s  based at least partly upon the sharpness control parameter Kshp. The system also includes a de-ringing control unit to adjust the ringing effect of the interpolated pixel based on a local image feature Kfreq, and an output module configured to output the adjusted interpolated pixel for display.

TECHNICAL FIELD OF THE INVENTION

The present invention generally relates to the field of digital imageprocessing, and more particularly to a system and process for rescalingdigital images for display.

BACKGROUND OF THE INVENTION

Digital images have become more popular in the field of image displaybecause they offer clarity and less distortion during processing.Furthermore, a wider range of image processing algorithms can be appliedto digital images. Interpolation is a common stage in image processingto improve the appearance of the processed image on the output imagingmedium. Interpolation is often performed during rescaling or resizing ofdigital images.

Rescaling or resizing of digital images includes magnification orreduction of image. For example, large screen displays have a nativeresolution that reaches or exceeds the well-known high-definition TV(HDTV) standard. In order to display a low-resolution digital image on alarge screen display, it is desirable to rescale the image to a fullscreen resolution.

Traditionally, linear interpolation techniques such as bilinear orbicubic interpolation are used to rescale digital images. The bilinearinterpolation method interpolates an input signal using a 2-tap filter.In this method, only the two pixels immediately on either side of thelocation of the new pixel are used. The bicubic interpolation methodinterpolates an input signal using a 4-tap filter. In this method, twopixels on either side of the location of the new pixel are used.

2-tap and 4-tap filters all have degradation in the high frequencyregion. These filters often suffer from image quality issues, such asblurring, aliasing, and staircase edges. 8-tap interpolation, such asthat performed by an 8-tap polyphase filter, improves reconstruction inthe high frequency region and reduces the staircase and aliasing issues.However, 8-tap interpolation introduces ringing artifacts along theedges, and the conventional 8-tap interpolation is not flexible insharpness control.

SUMMARY OF THE INVENTION

A digital video rescaling system is provided. The system includes animage data input configured to receive input support pixels y₁ to y_(n)and a sharpness control module configured to generate a sharpnesscontrol parameter Kshp. The system further includes an interpolatedpixel generator configured to use an adaptive interpolation kernel togenerate an interpolated pixel y_(s) based on the input support pixels,and adjust a sharpness of the interpolated pixel y_(s) based at leastpartly upon the sharpness control parameter Kshp. The system alsoincludes an output module configured to output the adjusted interpolatedpixel y_(s) for display.

A method of rescaling digital video is provided. The method includesreceiving input support pixels y₁ to y_(n) at an image data input,generating a sharpness control parameter Kshp at a sharpness controlmodule, and generating an interpolated pixel y_(s) based on the inputsupport pixels y₁ to y_(n) at an interpolated pixel generator. Themethod further includes adjusting a sharpness of the interpolated pixely_(s) based at least partly upon the sharpness control parameter Kshp atthe interpolated pixel generator, and outputting the adjustedinterpolated pixel y_(s) for display.

A digital video rescaling system is provided. The system includes animage data input configured to receive input support pixels y₁ to y_(n),and an interpolated pixel generator configured to use an adaptiveinterpolation kernel to generate an interpolated pixel value y_(s) basedon the input support pixels y₁ to y_(n). The system also includes ade-ringing control unit configured to modify the interpolated pixelvalue y_(s) adaptively to a local image feature Kfreq to generate anoutput y_(out), and an output module configured to output the outputy_(out) for display.

A method of rescaling digital video is provided. The method includesreceiving support pixels y₁ to y_(n) at an image data input, and usingan adaptive interpolation kernel to generate an interpolated pixel y_(s)based on the input support pixels y₁ to y_(n) at an interpolated pixelgenerator. The method also includes modifying the interpolated pixely_(s) adaptively to a local image feature Kfreq to generate an outputy_(out) at a de-ringing control unit, and outputting the output y_(out)for display.

Before undertaking the DETAILED DESCRIPTION OF THE INVENTION below, itmay be advantageous to set forth definitions of certain words andphrases used throughout this patent document: the terms “include” and“comprise,” as well as derivatives thereof, mean inclusion withoutlimitation; the term “or,” is inclusive, meaning and/or; the phrases“associated with” and “associated therewith,” as well as derivativesthereof, may mean to include, be included within, interconnect with,contain, be contained within, connect to or with, couple to or with, becommunicable with, cooperate with, interleave, juxtapose, be proximateto, be bound to or with, have, have a property of, or the like; and theterm “controller” means any device, system or part thereof that controlsat least one operation, such a device may be implemented in hardware,firmware or software, or some combination of at least two of the same.It should be noted that the functionality associated with any particularcontroller may be centralized or distributed, whether locally orremotely. Definitions for certain words and phrases are providedthroughout this patent document, those of ordinary skill in the artshould understand that in many, if not most instances, such definitionsapply to prior, as well as future uses of such defined words andphrases.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present disclosure and itsadvantages, reference is now made to the following description taken inconjunction with the accompanying drawings, in which like referencenumerals represent like parts:

FIG. 1 illustrates a digital video rescaling system according to anembodiment of this disclosure;

FIG. 2 illustrates the generation of an interpolated pixel based oneight input support pixels according to an embodiment of the presentdisclosure;

FIG. 3 illustrates an interpolation kernel generated according to anembodiment of the present disclosure;

FIG. 4 illustrates an interpolation kernel driven by a sharpness controlkernel according to an embodiment of the present disclosure;

FIG. 5 illustrates interpolation kernels having varying sharpnesscontrol values according to an embodiment of the present disclosure;

FIG. 6 illustrates the frequency responses of interpolation kernelshaving varying sharpness control values according to an embodiment ofthe present disclosure;

FIG. 7 illustrates an implementation of an adaptive 8-tap interpolationaccording to an embodiment of the present disclosure;

FIG. 8 illustrates an implementation of a de-ringing system according toan embodiment of the present disclosure; and

FIG. 9 illustrates a method of rescaling digital video according to anembodiment of the present disclosure.

DETAILED DESCRIPTION OF THE INVENTION

FIGS. 1 through 9, discussed below, and the various embodiments used todescribe the principles of the present disclosure in this patentdocument are by way of illustration only and should not be construed inany way to limit the scope of the disclosure. Those skilled in the artwill understand that the principles of the present disclosure may beimplemented in any suitably arranged system.

The present disclosure provides an effective system and method of videoimage rescaling. The present disclosure describes the use of adaptiveinterpolation kernels with sharpness and de-ringing control to reduceringing artifacts while maintaining the quality of the reconstruction inthe high frequency region. The sharpness and ringing effect of theinterpolated image are controlled using a sharpness control parameterand a de-ringing control parameter.

In some embodiments, a controllable interpolation kernel is used togenerate the interpolated outputs, which solves the issues of aliasingand staircase edges. With the adaptive sharpness and de-ringing control,the present disclosure provides a system and method to improve thesharpness of the output image without introducing ringing artifacts thatare a common issue in conventional 8-tap interpolation methods.

In particular embodiments, a controllable interpolation kernel with thefollowing key components is provided:

(1): an 8-tap interpolation filter to maintain the quality of thereconstruction in the high frequency region and solve aliasing andstaircase problems in the interpolated images;

(2) sharpness control functionality to generate the interpolated imageswith the visual qualities ranging from relative sharpness to softness;and

(3) de-ringing control functionality to adjust the levels of ringingeffects along the edges in the interpolated images.

The system and method of the present disclosure can be applied to ageneric video image processing system and can be used to both upscaleand downscale images with controllable sharpness levels.

FIG. 1 illustrates a digital video rescaling system 100 according to anembodiment of this disclosure.

As shown in FIG. 1, the rescaling system 100 includes an image datainput 101, an adaptive 8-tap interpolation unit 102, a de-ringingcontrol unit 103, and a local feature analysis unit 104. The finaloutput of the system 100 is sent from an image data output module 105.The image data input 101 receives a plurality of discrete sample valuesand sends the sample values to the adaptive 8-tap interpolation unit 102and the local feature analysis 104. The adaptive 8-tap interpolationunit 102 uses the discrete sample values received from the image datainput 101 to generate an interpolated pixel with controllable sharpnessvalue. The de-ringing control unit 103 receives the interpolated pixelfrom the adaptive 8-tap interpolation unit 102 and modifies theinterpolated pixel according to the local feature that was estimated bythe local feature analysis unit 104. The local feature analysis unit 104uses the discrete sample values received from the image data input 101to estimate local features used by the de-ringing control unit 103.

FIG. 2 illustrates the generation of an interpolated pixel 200 based oneight input support pixels 201-208 according to an embodiment of thepresent disclosure.

As shown in FIG. 2 in particular embodiments, the adaptive 8-tapinterpolation unit 102 uses controllable third order polynomialfunctions based on the eight input support pixels 201-208 to generatethe interpolated pixel 200.

In one embodiment, the interpolated pixel 200 can be calculated, forexample, by Equation 1 below:

$\begin{matrix}{y_{s} = {\sum\limits_{n = 1}^{8}\; {y_{n}*{{f_{n}(s)}.}}}} & \lbrack {{Eqn}.\mspace{14mu} 1} \rbrack\end{matrix}$

The eight control synthesis functions f_(n)(s) that can be expressed,for example, by Equations 2-9 below:

f ₁(s)=C(0,0)*s ³ +C(0,1)*s ² +C(0,2)*s+C(0,3),  [Eqn. 2],

f ₂(S)=C(1,0)*s ³ +C(1,1)*s ² +C(1,2)*s+C(1,3),  [Eqn. 3]

f ₃(S)=C(2,0)*s ³ +C(2,1)*s ² +C(2,2)*s+C(2,3),  [Eqn. 4]

f ₄(s)=C(3,0)*s ³ +C(3,1)*s ² +C(3,2)*s+C(3,3),  [Eqn. 5]

f ₅(s)=f ₄(1−s),  [Eqn. 6]

f ₆(s)=f ₃(1−s),  [Eqn. 7]

f ₇(s)=f ₂(1−s), and  [Eqn. 8]

f ₈(s)=f ₁(1−s).  [Eqn. 9]

The C(i,j) coefficient metrics of the above control synthesis functionscan be calculated, for example, by Equation 10 below:

C(i,j)=A(i,j)+Kshp*B(i,j),  [Eqn. 10]

In Equation 10,

$A = \begin{bmatrix}{a( {0,0} )} & {a( {0,1} )} & {a( {0,2} )} & {a( {0,3} )} \\{a( {1,0} )} & {a( {1,1} )} & {a( {1,2} )} & {a( {1,3} )} \\{a( {2,0} )} & {a( {2,1} )} & {a( {2,2} )} & {a( {2,3} )} \\{a( {3,0} )} & {a( {3,1} )} & {a( {3,2} )} & {a( {3,3} )}\end{bmatrix}$ and $B = \begin{bmatrix}{b( {0,0} )} & {b( {0,1} )} & {b( {0,2} )} & {b( {0,3} )} \\{b( {1,0} )} & {b( {1,1} )} & {b( {1,2} )} & {b( {1,3} )} \\{b( {2,0} )} & {b( {2,1} )} & {b( {2,2} )} & {b( {2,3} )} \\{b( {3,0} )} & {b( {3,1} )} & {b( {3,2} )} & {b( {3,3} )}\end{bmatrix}$

are two coefficient matrices, for example, used to generateinterpolation kernel and sharpness control kernel.

The coefficient matrices A and B are defined, for example, as shown inEquations 11 and 12 below:

$\begin{matrix}{{A = \begin{bmatrix}{- 21} & 52 & {- 32} & 0 \\52 & {- 150} & 97 & 1 \\{- 154} & 412 & {- 256} & 0 \\304 & {- 587} & 28 & 254\end{bmatrix}},{and}} & \lbrack {{Eqn}.\mspace{14mu} 11} \rbrack \\{B = {\begin{bmatrix}{- 9} & 21 & {- 11} & {- 2} \\15 & {- 38} & 18 & 3 \\{- 32} & 69 & {- 23} & {- 11} \\51 & {- 88} & 5 & 21\end{bmatrix}.}} & \lbrack {{Eqn}.\mspace{14mu} 12} \rbrack\end{matrix}$

Of course one of ordinary skill in the art would recognize that matricesA and B are just one example of coefficient matrices that may be used togenerate an 8-tap interpolation kernel and an 8-tap sharpness controlkernel, respectively, and that any number of coefficient matrices may beused without departing from the scope or spirit of the presentdisclosure.

Accordingly, the interpolated pixel 200 also can be calculated, forexample, by Equation 13 below:

$\begin{matrix}{{{y_{s}(s)} = {\sum\limits_{n = 1}^{8}\; {y_{n}*{f_{n}( {s,{Kshp}} )}}}},} & \lbrack {{Eqn}.\mspace{14mu} 13} \rbrack\end{matrix}$

where y_(n), n=(1 . . . 8) are the eight support pixels 201-208 from theimage data input 101. s is the phase of the interpolation which is thedistance from interpolation position to the position of the supportpixel y₄. The range of phase is from 0 to 1. The number of phases can bedefined by the precision of the interpolation. f_(n)(s,Kshp) (n=1 . . .8) are eight control synthesis functions that can be expressed, forexample, by Equations 14-21 below:

f ₁(s,Kshp)=(a(0,0)+Kshp*b(0,0))*s ³+(a(0,1)+Kshp*b(0,1))*s²+(a(0,2)+Kshp*b(0,2)*s+(a(0,3)+Kshp*b(0,3))  [Eqn. 14]

f ₂(s,Kshp)=(a(1,0)+Kshp*b(1,0))*s ³+(a(1,1)+Kshp*b(1,1))*s²+(a(1,2)+Kshp*b(1,2)*s+(a(0,3)+Kshp*b(1,3))  [Eqn. 15]

f ₃(s,Kshp)=(a(2,0)+Kshp*b(2,0))*s ³+(a(2,1)+Kshp*b(2,1))*s²+(a(2,2)+Kshp*b(2,2)*s+(a(2,3)+Kshp*b(2,3))  [Eqn. 16]

f ₄(s,Kshp)=(a(3,0)+Kshp*b(3,0))*s ³+(a(3,1)+Kshp*b(3,1))*s²+(a(3,2)+Kshp*b(3,2)*s+(a(3,3)+Kshp*b(3,3))  [Eqn. 17]

f ₅(s,Kshp)=f ₄((1−s),Kshp),  [Eqn. 18]

f ₆(s,Kshp)=f ₃((1−s),Kshp),  [Eqn. 19]

f ₇(s,Kshp)=f ₂((1−s),Kshp), and  [Eqn. 20]

f ₈(s,Kshp)=((1−s),Kshp).  [Eqn. 21]

FIG. 3 illustrates an interpolation kernel 300 generated according to anembodiment of the present disclosure.

In this particular embodiment, the interpolation kernel 300 wasgenerated by the coefficient matrix A.

FIG. 4 illustrates an interpolation kernel 401 driven by a sharpnesscontrol kernel 403 according to an embodiment of the present disclosure.

As shown in FIG. 4, an interpolation kernel 401 is driven by a sharpnesscontrol kernel 403. The interpolation kernel 401 may be generated, forexample, by coefficient matrix A, and the sharpness control kernel 403may be generated, for example, by coefficient matrix B. The sharpnesscontrol kernel 403 is combined with the interpolation kernel 401 togenerate a resulting interpolation kernel 405 having sharpness control.In a particular embodiment, EAT in Equation 13 is the sharpness controlparameter used to adjust the sharpness of the interpolated pixel.

FIG. 5 illustrates adaptive interpolation kernels having varyingsharpness control values according to an embodiment of the presentdisclosure.

FIG. 6 illustrates the frequency responses of adaptive interpolationkernels having varying sharpness control values according to anembodiment of the present disclosure.

As shown in FIGS. 5 and 6, the adaptive interpolation kernels are drivenby varying sharpness control values, and their frequency responses varywith the sharpness control values. From the frequency responses, it canbe seen that the magnitudes of the high frequency region are adjustedaccordingly to the sharpness control parameter.

FIG. 7 illustrates an implementation of an adaptive 8-tap interpolationaccording to an embodiment of the present disclosure.

In this embodiment, coefficient A and B are stored in two registerarrays 701 and 703. The coefficient C is calculated in calculation unit705, for example, by C=A+Kshp*B. Kshp is provided by a sharpness controlmodule 707. The coefficient C is passed to synthesis function unit 709to generate the synthesis functions f_(i)(s) (i=1 . . . 8). The f_(i)(s)are then used as filter coefficients in interpolated pixel generator 711to generate the interpolated pixel y_(s) by an 8-tap filter.

As shown in FIG. 1, the process at de-ringing control unit 103 is usedto modify the interpolated pixel adaptively to the local image feature,the local image feature being related to the local frequencycharacteristics. In particular embodiments, the control in the highfrequency region should be less to maintain quality reconstruction inthe high frequency region. In the edge or low frequency region, thecontrol should be higher to reduce the ringing effect.

FIG. 8 illustrates an implementation of a de-ringing process accordingto an embodiment of the present disclosure.

FIG. 8 shows a local frequency analysis unit 801, a local max/minanalysis unit 802, a comparator 803 and a de-ringing control unit 804.The local frequency analysis 801 is used to calculate a feature valuethat is related to the local frequency. In some embodiments, the localfeature is estimated, for example, using Equation 22 below:

Kfreq=min(dev1,dev2,dev3,dev4)/N,  [Eqn. 22]

where dev1, dev2, dev3 and dev4 are defined as shown in Equations 23-26below:

dev1=max(|y ₁−2*y ₂ +y ₃ |,|y ₂−2*y ₃ +y ₄|),  [Eqn. 23]

dev2=max(|y ₃−2*y ₄ +y ₅ |,|y ₄−2*y ₅ +y ₆|)  [Eqn. 24]

dev3=max(|y ₅−2*y ₆ +y ₇ |,|y ₆−2*y ₇ +y ₈|), and  [Eqn. 25]

dev4=min(|y ₂ −y ₄ |,|y ₃ −y ₅|).  [Eqn. 26]

N is a constant value used to normalize Kfreq so that Kfreq is in therange of [0,1]. Of course one of ordinary skill in the art wouldrecognize that this is just one way of determining the local feature andthat other means of determining the local feature may be utilizedwithout departing from the scope or spirit of the present disclosure.

The local max/min analysis unit 802 is used to discriminate between thelarger and smaller value of the support pixels y₄ and y₅ as shown inEquations 27 and 28 below:

Lmax=max(y ₄ y ₅), and  [Eqn. 27]

Lmin=min(y ₄ ,y ₅).  [Eqn. 28]

The outputs of the local max/min analysis unit 802 are then comparedwith the output of the adaptive 8-tap interpolation unit 102 (y_(s)) inthe comparator 803 to generate the output (y_(m)) as shown in Equation29 below:

$\begin{matrix}{y_{m} = \{ \begin{matrix}{L\; \max} & {{if}\mspace{14mu} ( {y_{s} > {L\; \max}} )} \\{L\; \min} & {{if}\mspace{14mu} ( {y_{s} < {L\; \min}} )} \\y_{s} & {{else}.}\end{matrix} } & \lbrack {{Eqn}.\mspace{14mu} 29} \rbrack\end{matrix}$

The outputs y_(s) and y_(m) are then subtracted and multiplied by thelocal image feature Kfreq in the de-ringing control unit 804 to generatethe final output y_(out) as shown in Equation 30 below:

y _(out) =Kfreq*(y _(s) −y _(m))+y _(m)  [Eqn. 30]

FIG. 9 illustrates a method 900 of rescaling digital video according toan embodiment of the present disclosure.

As shown in FIG. 9, the method 900 includes receiving input supportpixels y₁ to y_(n) (block 901), generating a sharpness control parameterKshp (block 903), and generating an interpolated pixel y_(s) based onthe input support pixels y₁ to y_(n) (block 905). The method 900 alsoincludes adjusting a sharpness of the interpolated pixel y_(s) based atleast partly upon the sharpness control parameter Kshp (block 907). Themethod 900 further includes generating a local image feature Kfreq(block 909) and modifying the interpolated pixel y_(s) adaptively to thelocal image feature Kfreq to generate an output y_(out) (block 911). Themethod 900 also includes outputting the output y_(out) for display(block 913).

Although the present disclosure has been described with an exemplaryembodiment, various changes and modifications may be suggested to oneskilled in the art. It is intended that the present disclosure encompasssuch changes and modifications as fall within the scope of the appendedclaims.

1. A digital video rescaling system comprising: an image data inputconfigured to receive input support pixels y₁ to y_(n); a sharpnesscontrol module configured to generate a sharpness control parameterKshp; an interpolated pixel generator configured to use an 8-tap filterto generate an interpolated pixel y_(s) based on the input supportpixels, and adjust a sharpness of the interpolated pixel y_(s) based atleast partly upon the sharpness control parameter Kshp; and an outputmodule configured to output the adjusted interpolated pixel y_(s) fordisplay.
 2. A system in accordance with claim 1 wherein the interpolatedpixel generator is configured to generate the interpolated pixel y_(s)using third order polynomial functions based at least partly upon eightinput support pixels y₁ to y₈.
 3. A system in accordance with claim 1wherein the interpolated pixel y_(s) is generated as follows:${{y_{s}(s)} = {\sum\limits_{n = 1}^{8}\; {y_{n}*{f_{n}( {s,{Kshp}} )}}}},$where y_(n), n=(1 . . . 8) are eight support pixels. S is the phase ofthe interpolation which is the distance from interpolation position tothe position of the support pixel y₄. f_(n)(s,Kshp) (n=1 . . . 8) areeight control synthesis functions that can be expressed as follows:f ₁(s,Kshp)=(a(0,0)+Kshp*b(0,0))*s ³+(a(0,1)+Kshp*b(0,1))*s²+(a(0,2)+Kshp*b(0,2)*s+(a(0,3)+Kshp*b(0,3))f ₂(s,Kshp)=(a(1,0)+Kshp*b(1,0))*s ³+(a(1,1)+Kshp*b(1,1))*s²+(a(1,2)+Kshp*b(1,2)*s+(a(0,3)+Kshp*b(1,3))f ₃(s,Kshp)=(a(2,0)+Kshp*b(2,0))*s ³+(a(2,1)+Kshp*b(2,1))*s²+(a(2,2)+Kshp*b(2,2)*s+(a(2,3)+Kshp*b(2,3))f ₄(s,Kshp)=(a(3,0)+Kshp*b(3,0))*s³+(a(3,1)+Kshp*b(3,1))*s²+(a(3,2)+Kshp*b(3,2)*s+(a(3,3)+Kshp*b(3,3))f ₅(s,Kshp)=f ₄((1−s),Kshp),f ₆(s,Kshp)=f ₃((1−s),Kshp),f ₇(s,Kshp)=f ₂((1−s),Kshp), andf ₈(s,Kshp)=f ₁((1−s),Kshp). $A = \begin{bmatrix}{a( {0,0} )} & {a( {0,1} )} & {a( {0,2} )} & {a( {0,3} )} \\{a( {1,0} )} & {a( {1,1} )} & {a( {1,2} )} & {a( {1,3} )} \\{a( {2,0} )} & {a( {2,1} )} & {a( {2,2} )} & {a( {2,3} )} \\{a( {3,0} )} & {a( {3,1} )} & {a( {3,2} )} & {a( {3,3} )}\end{bmatrix}$ and $B = \begin{bmatrix}{b( {0,0} )} & {b( {0,1} )} & {b( {0,2} )} & {b( {0,3} )} \\{b( {1,0} )} & {b( {1,1} )} & {b( {1,2} )} & {b( {1,3} )} \\{b( {2,0} )} & {b( {2,1} )} & {b( {2,2} )} & {b( {2,3} )} \\{b( {3,0} )} & {b( {3,1} )} & {b( {3,2} )} & {b( {3,3} )}\end{bmatrix}$ are two coefficient matrices.
 4. A system in accordancewith claim 3 wherein the coefficient matrices A and B are defined asfollows: $\begin{matrix}{{A = \begin{bmatrix}{- 21} & 52 & {- 32} & 0 \\52 & {- 150} & 97 & 1 \\{- 154} & 412 & {- 256} & 0 \\304 & {- 587} & 28 & 254\end{bmatrix}},{and}} \\{B = {\begin{bmatrix}{- 9} & 21 & {- 11} & {- 2} \\15 & {- 38} & 18 & 3 \\{- 32} & 69 & {- 23} & {- 11} \\51 & {- 88} & 5 & 21\end{bmatrix}.}}\end{matrix}$
 5. A method of rescaling digital video, the methodcomprising: receiving input support pixels y₁ to y_(n) at an image datainput; generating a sharpness control parameter Kshp at a sharpnesscontrol module; generating an interpolated pixel y_(s) based on theinput support pixels y₁ to y_(n) at an 8-tap filter; adjusting asharpness of the interpolated pixel y_(s) based at least partly upon thesharpness control parameter Kshp at the interpolated pixel generator;and outputting the adjusted interpolated pixel y_(s) for display.
 6. Amethod in accordance with claim 5 wherein generating the interpolatedpixel y_(s) comprises using third order polynomial functions based atleast partly upon eight input support pixels y₁ to y₈.
 7. A method inaccordance with claim 5 wherein generating the interpolated pixel y_(s)comprises using the following relationship:${{y_{s}(s)} = {\sum\limits_{n = 1}^{8}\; {y_{n}*{f_{n}( {s,{Kshp}} )}}}},$where y_(n), n=(1 . . . 8) are eight support pixels. S is the phase ofthe interpolation which is the distance from interpolation position tothe position of the support pixel y₄. f_(n)(s,Kshp) (n=1 . . . 8) areeight control synthesis functions that can be expressed as follows:f ₁(s,Kshp)=(a(0,0)+Kshp*b(0,0))*s ³(a(0,1)+Kshp*b(0,1))*s²+(a(0,2)+Kshp*b(0,2)*s+(a(0,3)+Kshp*b(0,3))f ₂(s,Kshp)=(a(1,0)+Kshp*b(1,0))*s ³+(a(1,1)+Kshp*b(1,1))*s²+(a(1,2)+Kshp*b(1,2)*s+(a(0,3)+Kshp*b(1,3))f ₃(s,Kshp)=(a(2,0)+Kshp*b(2,0))*s ³+(a(2,1)+Kshp*b(2,1))*s²+(a(2,2)+Kshp*b(2,2)*s+(a(2,3)+Kshp*b(2,3))f _(a)(s,Kshp)=(a(3,0)+Kshp*b(3,0))*s ³+(a(3,1)+Kshp*b(3,1))*s²+(a(3,2)+Kshp*b(3,2)*s+(a(3,3)+Kshp*b(3,3))f ₅(s,Kshp)=f ₄((1−s),Kshp),f ₆(s,Kshp)=f ₃((1−s),Kshp),f ₇(s,Kshp)=f ₂((1−s),Kshp), andf ₈(s,Kshp)=f ₁((1−s),Kshp). $A = \begin{bmatrix}{a( {0,0} )} & {a( {0,1} )} & {a( {0,2} )} & {a( {0,3} )} \\{a( {1,0} )} & {a( {1,1} )} & {a( {1,2} )} & {a( {1,3} )} \\{a( {2,0} )} & {a( {2,1} )} & {a( {2,2} )} & {a( {2,3} )} \\{a( {3,0} )} & {a( {3,1} )} & {a( {3,2} )} & {a( {3,3} )}\end{bmatrix}$ and $B = \begin{bmatrix}{b( {0,0} )} & {b( {0,1} )} & {b( {0,2} )} & {b( {0,3} )} \\{b( {1,0} )} & {b( {1,1} )} & {b( {1,2} )} & {b( {1,3} )} \\{b( {2,0} )} & {b( {2,1} )} & {b( {2,2} )} & {b( {2,3} )} \\{b( {3,0} )} & {b( {3,1} )} & {b( {3,2} )} & {b( {3,3} )}\end{bmatrix}$ are two coefficient matrices.
 8. A method in accordancewith claim 7 wherein the coefficient matrices A and B are defined asfollows: $\begin{matrix}{{A = \begin{bmatrix}{- 21} & 52 & {- 32} & 0 \\52 & {- 150} & 97 & 1 \\{- 154} & 412 & {- 256} & 0 \\304 & {- 587} & 28 & 254\end{bmatrix}},{and}} \\{B = {\begin{bmatrix}{- 9} & 21 & {- 11} & {- 2} \\15 & {- 38} & 18 & 3 \\{- 32} & 69 & {- 23} & {- 11} \\51 & {- 88} & 5 & 21\end{bmatrix}.}}\end{matrix}$
 9. A digital video rescaling system comprising: an imagedata input configured to receive input support pixels y₁ to y_(n); aninterpolated pixel generator configured to use an 8-tap filter togenerate an interpolated pixel value y_(s) based on the input supportpixels y₁ to y_(n); a de-ringing control unit configured to modify theinterpolated pixel y_(s) adaptively to a local image feature Kfreq togenerate an output y_(out); and an output module configured to outputthe output y_(out) for display.
 10. A system in accordance with claim 9wherein the local image feature Kfreq is related to local frequencycharacteristics.
 11. A system in accordance with claim 9 furthercomprising: a local frequency analysis unit configured to calculate thelocal image feature Kfreq; a local max/min analysis unit configured todistinguish between a larger and a smaller value of two support pixelsy_(a) and y_(b) and generate an output Lmax and Lmin; and a comparatorconfigured to compare the interpolated pixel value y_(s) with the outputLmax and Lmin and generate a comparison result y_(m).
 12. A system inaccordance with claim 11 further wherein the comparator is configured togenerate the comparison result y_(m) as follows:$y_{m} = \{ \begin{matrix}{L\; \max} & {{if}\mspace{14mu} ( {y_{s} > {L\; \max}} )} \\{L\; \min} & {{if}\mspace{14mu} ( {y_{s} < {L\; \min}} )} \\y_{s} & {{else}.}\end{matrix} $
 13. A system in accordance with claim 11 furtherwherein the de-ringing control unit is further configured to: subtractthe comparison result y_(m) from the interpolated pixel value y_(s);multiply the difference by the local image feature Kfreq; and add theproduct to comparison result y_(m) to generate g_(out).
 14. A system inaccordance with claim 9 wherein the local frequency analysis unit isconfigured to calculate the local image feature Kfreq as follows:Kfreq=min(dev1,dev2,dev3,dev4)/N, where dev1, dev2, dev3 and dev4 aredefined as follows:dev1=max(|y ₁−2*y ₂ +y ₃ |,|y ₂−2*y ₃ +y ₄|),dev2=max(|y ₃−2*y ₄ +y ₅ |,|y ₄−2*y ₅ +y ₆|),dev3=max(|y ₅−2*y ₆ +y ₇ |,|y ₆−2*y ₇ +y ₈|), anddev4=min(|y ₂ −y ₄ |,|y ₃ −y ₅|), where N is a constant value used tonormalize Kfreq so that Kfreq is in the range of [0,1].
 15. A method ofrescaling digital video, the method comprising: receiving support pixelsy₁ to y_(n) at an image data input; using an 8-tap filter to generate aninterpolated pixel y_(s) based on the input support pixels y₁ to y_(n)at an interpolated pixel generator; modifying the interpolated pixely_(s) adaptively to a local image feature Kfreq to generate an outputy_(out) at a de-ringing control unit; and outputting the output y_(out)for display.
 16. A method in accordance with claim 15 wherein the localimage feature Kfreq is related to local frequency characteristics.
 17. Amethod in accordance with claim 15 further comprising: distinguishingbetween a larger and a smaller value of two support pixels y_(a) andy_(b) and generating an output Lmax and Lmin at a local max/min analysisunit; and comparing the interpolated pixel value y_(s) with the outputLmax and Lmin and generating a comparison result y_(m) at a comparator.18. A method in accordance with claim 17 further wherein the comparisonresult y_(m) is generated as follows: $y_{m} = \{ \begin{matrix}{L\; \max} & {{if}\mspace{14mu} ( {y_{s} > {L\; \max}} )} \\{L\; \min} & {{if}\mspace{14mu} ( {y_{s} < {L\; \min}} )} \\y_{s} & {{else}.}\end{matrix} $
 19. A method in accordance with 17 furthercomprising: subtracting the comparison result y_(m) from theinterpolated pixel value y_(s); multiplying the difference by the localimage feature Kfreg; and adding the product to comparison result y_(m)to generate y_(out) at the de-ringing control unit.
 20. A method inaccordance with claim 15 wherein calculating the local image featureKfreq comprises using the following relationship:Kfreq=min(dev1,dev2,dev3,dev4)/N, where dev1, dev2, dev3 and dev4 aredefined as follows:dev1=max(|y ₁−2*y ₂ +y ₃ |,|y ₂−2*y ₃ +y ₄|),dev2=max(|y ₃−2*y ₄ +y ₅ |,|y ₄−2*y ₅ +y ₆|),dev3=max(|y ₅−2*y ₆ +y ₇ |,|y ₆−2*y ₇ +y ₈|), anddev4=min(|y ₂ −y ₄ |,|y ₃ −y ₅|), where N is a constant value used tonormalize Kfreq so that Kfreq is in the range of [0,1].